Abstract

The success of NASA's Mars Exploration Rovers has demonstrated the
important benefits that mobility adds to planetary exploration.  Very
soon, mission requirements will impose  that planetary exploration
rovers drive autonomously in unknown terrain. This will require an
evolution of the methods and technologies currently used. This paper
presents  our approach to 3D terrain reconstruction from large sparse
range data sets, and the data reduction achieved through decimation.
The outdoor experimental results demonstrate the effectiveness of the
reconstructed terrain  model for different types of terrain. We also
present a first attempt to classify the terrain based on the scans
properties.